Integrating single-cell RNA-seq and bulk RNA-seq to construct a neutrophil prognostic model for predicting prognosis and immune response in oral squamous cell carcinoma

Abstract

Abstract Background Oral squamous cell carcinoma (OSCC) is an aggressive malignancy with poor prognosis. Neutrophil infiltration has been associated with unfavorable outcomes in OSCC, but the underlying molecular mechanisms remain unclear. Methods This study integrated single-cell transcriptomics (scRNA-seq) with bulk RNA-seq data to analyze neutrophil infiltration patterns in OSCC and identify key gene modules using weighted gene co-expression network analysis (hdWGCNA). A prognostic model was developed based on univariate and Lasso-Cox regression analyses, stratifying patients into high- and low-risk groups. Immune landscape and drug sensitivity analyses were conducted to explore group-specific differences. Additionally, Mendelian randomization analysis was employed to identify genes causally related to OSCC progression. Results Several key pathways associated with neutrophil interactions in OSCC progression were identified, leading to the construction of a prognostic model based on significant module genes. The model demonstrated strong predictive performance in distinguishing survival rates between high- and low-risk groups. Immune landscape analysis revealed significant differences in cell infiltration patterns and TIDE scores between the groups. Drug sensitivity analysis highlighted differences in drug responsiveness between high- and low-risk groups. Conclusion This study elucidates the critical role of neutrophils and their associated gene modules in OSCC progression. The prognostic model provides a novel reference for patient stratification and targeted therapy. These findings offer potential new targets for OSCC diagnosis, prognosis, and immunotherapy.

Keywords

• Oral squamous cell carcinoma
• Neutrophils
• Immune landscape
• Risk model
• Biomarkers